R package erboost: Nonparametric Multiple Expectile Regression via ER-Boost. Expectile regression is a nice tool for estimating the conditional expectiles of a response variable given a set of covariates. This package implements a regression tree based gradient boosting estimator for nonparametric multiple expectile regression.
Keywords for this software
References in zbMATH (referenced in 6 articles )
Showing results 1 to 6 of 6.
- Chen, Tuo; Su, Zhihua; Yang, Yi; Ding, Shanshan: Efficient estimation in expectile regression using envelope models (2020)
- Farooq, Muhammad; Steinwart, Ingo: Learning rates for kernel-based expectile regression (2019)
- Yue, Mu; Li, Jialiang; Cheng, Ming-Yen: Two-step sparse boosting for high-dimensional longitudinal data with varying coefficients (2019)
- Farooq, Muhammad; Steinwart, Ingo: An SVM-like approach for expectile regression (2017)
- Waldmann, Elisabeth; Sobotka, Fabian; Kneib, Thomas: Bayesian regularisation in geoadditive expectile regression (2017)
- Yang, Yi; Zou, Hui: Nonparametric multiple expectile regression via ER-Boost (2015)